Spatial Correlation Characteristics and Inner-mechanism of Urbanization Dataset in the Yangtze River Delta (1995-2015)
LI Mengdi1,2CUI Yaoping*1,2LIU Xuan2LI Dongyang2FAN Lin2ZHAO Wei2
1 Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions (Henan University)，Ministry of Education，Kaifeng 475004，China2 College of Environment and Planning，Henan University，Kaifeng 475004，China
DOI:10.3974/geodb.2020.09.09.V1
Published:Dec. 2020
Visitors：2858 Data Files Downloaded：198
Data Downloaded：13.04 MB Citations：
Key Words：
Yangtze River Delta,Urbanization Spatial Correlation Intensity,Urbanization Comprehensive Development,Acta Geographica Sinica
Abstract：
The Yangtze River Delta (YRD) includes 41 prefecture-level cities in Shanghai, Jiangsu, Zhejiang, and Anhui Provinces of China. Spatial Correlation Characteristics and Inner-mechanism of Urbanization Dataset in the Yangtze River Delta is consisted of the following data: (1) the Urbanization spatial Correlation Intensity (UCI) data in YRD ; (2) the Moran’s I and polarization index data in YRD; (3) growth rate of economic, population, built-up area and the Urbanization Speed (US) data of the core cities; (4) Urbanization Speed (US) data in YRD; 5) Urbanization comprehensive Development (UD) data of main cities in YRD. The dataset is archived in one single file in .xlsx data format with 67.4 KB. The analysis paper based on the dataset was published in Acta Geographica Sinica, Vol. 75, No.6, 2020.Browse
Foundation Item：
National Natural Science Foundation of China (42071415, 41671425); Henan Natural Science Foundation (202300410049)
Data Citation：
LI Mengdi, CUI Yaoping*, LIU Xuan, LI Dongyang, FAN Lin, ZHAO Wei.Spatial Correlation Characteristics and Inner-mechanism of Urbanization Dataset in the Yangtze River Delta (1995-2015)[J/DB/OL]. Digital Journal of Global Change Data Repository, 2020. https://doi.org/10.3974/geodb.2020.09.09.V1.
LI Mengdi, CUI Yaoping, LIU Xuan, et al. Spatial correlation characteristics and inner-mechanism of urbanization dataset in the Yangtze River Delta [J]. Journal of Global Change Data & Discovery, 2020, 4(4): 354-362. https://doi.org/10.3974/geodp.2020.04.06.
References：
[1] Liu, H. M., Fang, C. L., Miao, Y., et al. Spatio-temporal evolution of population and urbanization in the countries along the Belt and Road 1950-2050[J]. Journal of Geographical Sciences, 2018, 28(7): 919-936.
[2] Boyd, J. P., Mahutga, M. C., Smith, D. A. Measuring centrality and power recursively in the World City Network: A reply to Neal[J]. Urban Studies, 2013, 50(8): 1641-1647.
[3] Liu, S.B.,Yang, S., Wang, Z. Characteristics and formation mechanism of China's provincial urbanization spatial correlation based on population flow. ActaGeographicaSinica,2019,74(4): 648-663.
[4] Wang, Z., Yang, S., Gong, F.H., et al. Identification of urban agglomerations deformation structure based on urbanflow space: a case study of the Yangtze River Delta urban agglomeration. ScientiaGeographicaSinica, 2017, 37(9):1337-1344.
Data Product:
| ID |
Data Name |
Data Size |
Operation |
| 0 | Datapaper_SpatialCorrelationUrbanYRD_1995-2015.pdf | 3422.00kb | DownLoad |
| 1 |
SpatialCorrelationUrbanYRD_1995-2015.xlsx |
67.46KB |
|